|Year : 2021 | Volume
| Issue : 2 | Page : 114-121
Prevalence and correlates of metabolic syndrome among psychiatric inpatients at a tertiary care center
Natasha Celia Saldanha1, Sivaprakash Balasundaram2, Sukanto Sarkar3, Mohamed Hanifah4
1 Department of Psychiatry, St. John's Medical College Hospital, Bengaluru, Karnataka, India
2 Department of Psychiatry, Mahatma Gandhi Medical College and Research Institute, Sri Balaji Vidyapeeth, Puducherry, India
3 Department of Psychiatry, All India Institute of Medical Sciences, Kalyani, West Bengal, India
4 Department of General Medicine, Mahatma Gandhi Medical College and Research Institute, Sri Balaji Vidyapeeth, Puducherry, India
|Date of Submission||21-Sep-2021|
|Date of Decision||09-Oct-2021|
|Date of Acceptance||16-Oct-2021|
|Date of Web Publication||12-Jan-2022|
Dr. Natasha Celia Saldanha
Department of Psychiatry, St. John's Medical College Hospital, Bengaluru - 560 034, Karnataka
Source of Support: None, Conflict of Interest: None
Background: Metabolic syndrome (MetS) is a complex illness with interconnected physiological, clinical, and metabolic factors. MetS is more prevalent in patients with mental illness than in the general population and contributes to greater morbidity and mortality. Thus we, studied the prevalence and correlates of MetS in psychiatric inpatients.
Materials and Methods: The study is an observational cross-sectional study conducted at a tertiary care center. All consecutive patients (n = 185) admitted to the department of Psychiatry were enrolled after informed consent. Sociodemographic data, clinical data, and treatment details were collected. The WHO Global Physical Activity Questionnaire was administered to assess the level of physical activity; MetS was diagnosed as per the International Diabetes Federation criteria.
Results: The prevalence of MetS was 22.7% among the study participants. The prevalence of MetS was significantly associated with higher age, urban domicile status, and middle and upper socioeconomic classes. Clinical characteristics such as longer duration of illness, comorbid substance use disorders, and treatment regimens with only antipsychotics medications were associated with higher likelihood of MetS. There was a higher prevalence of MetS among subjects with lower level of physical activity.
Conclusion: One-fourth of the psychiatric inpatients had MetS. Guidelines specific to the Indian context need to be developed for the screening and monitoring of psychiatric patients with reference to MetS. Promotion of physical well-being and physical activity among patients with mental disorders is likely to contribute to a better overall outcome.
Keywords: Anti-psychotics, metabolic syndrome, physical activity, psychiatric inpatients
|How to cite this article:|
Saldanha NC, Balasundaram S, Sarkar S, Hanifah M. Prevalence and correlates of metabolic syndrome among psychiatric inpatients at a tertiary care center. Telangana J Psychiatry 2021;7:114-21
|How to cite this URL:|
Saldanha NC, Balasundaram S, Sarkar S, Hanifah M. Prevalence and correlates of metabolic syndrome among psychiatric inpatients at a tertiary care center. Telangana J Psychiatry [serial online] 2021 [cited 2022 Nov 28];7:114-21. Available from: https://tjpipstsb.org/text.asp?2021/7/2/114/335642
| Introduction|| |
People diagnosed with mental disorders experience a high burden of mortality at both the individual and population level. It is well known that people with mental disorders have elevated mortality compared to the general population. Severe mental illness is associated with a threefold increased risk of early death and curtails life expectancy by roughly 10–20 years. The higher rates of mortality in this population cannot be explained only by increased rates of unnatural causes of death such as suicide and accidents. More than 60% of this excess mortality is due to comorbid physical conditions, including cardiovascular disease and stroke., Factors predisposing people with severe mental illness to cardiovascular disease include antipsychotic medications and unhealthy lifestyles as well as a reduced likelihood to receive standard levels of medical care. It has also been observed that the prevalence of metabolic syndrome (MetS) is greater in people with mental disorders than that in the general population.
MetS is a complex lifestyle-dependent illness with interconnected physiological, biochemical, and clinical factors. The concept of this syndrome has gradually evolved over time with changing definitions; however, the core disturbances – namely glucose intolerance, obesity, hypertension, and dyslipidemia – remain vital diagnostic criteria. MetS is a major predictor of mortality and morbidity.
MetS is a major and escalating public health problem. A study conducted at Chennai, India, documented a prevalence rate of 11.2%, whereas a study from the USA noted a prevalence of 34.7%. Several meta-analyses have documented that people with severe mental illnesses have an increased risk for developing MetS compared with the general population.,, This finding is exemplified in a study among patients with schizophrenia. Similar findings have been affirmed among patients with bipolar disorder and among patients with major depressive disorder., A North Indian study found a higher prevalence of MetS among psychiatric inpatients (37.8%) than that in the general population.
Level of physical activity has been studied as a risk factor in the context of MetS among psychiatric patients. Clinical experience and research confirm that patients with severe mental illness are physically less active.,,, Studies have explored the association between physical activity and MetS among patients with mental illness.,, However, research on this theme is scarce in India.
There are notable gaps in the available literature on MetS in mental illness. Expansion of the knowledge base with regard to the prevalence and determinants of MetS among psychiatric patients is likely to contribute toward better preventive and management strategies. Thus, this study was undertaken to estimate the prevalence of MetS in a tertiary care hospital in Puducherry, India, and to study the sociodemographic, clinical, and treatment correlates.
| Materials and Methods|| |
Study setting, design, and participants
An observational cross-sectional study was conducted in the department of Psychiatry of a tertiary care center in Puducherry, India, from February 2017 to March 2018. The study was approved by the institutional human ethics committee. All consecutive patients aged 18 years and above getting admitted to the department of Psychiatry were included in the study after informed consent. Patients with major neurocognitive disorders, those with intellectual disability, those with inability to comprehend and respond to questions asked, those with insufficient cooperation, pregnant women, and patients without a psychiatric diagnosis according to DSM-5 at the time of discharge were all excluded from the study. With regard to patients getting admitted more than once in the study period, data were obtained only from the first admission.
A semi-structured pro forma was used to collect information pertaining to sociodemographic details, which included age, gender, marital status, education, occupation, area of domicile and socioeconomic status according to modified Kuppuswamy scale. Clinical variables such as psychiatric diagnosis, duration of illness, and treatment variables (based on available records) were also documented. Blood pressure, waist circumference, fasting blood sugar, triglycerides, and high-density lipoprotein cholesterol were measured. MetS was diagnosed based on the International Diabetes Federation criteria, as follows: abdominal obesity ≥90 cm (men) and ≥80 cm (women), blood pressure systolic ≥130 mmHg or diastolic ≥85 mmHg, triglycerides >150 mg/dL, high-density lipoprotein <40 mg/dL (men) and <50 mg/dL (women), and fasting blood sugar ≥100 mg/dL; three abnormal findings out of five would qualify a person for the diagnosis of MetS. Rating of habitual physical activity was done using the Global Physical Activity Questionnaire (GPAQ) developed by the World Health Organization.
Descriptive statistics was used to describe the sample in terms of mean and standard deviation for continuous variables and frequency and percentage for categorical variables. Psychiatric diagnoses were clustered into five diagnostic groups and only those with a single psychiatric diagnosis were included for analysis (n = 160). Chi-square test and t-test were done to ascertain the association between MetS and the various variables. Binary logistic regression analysis was performed, and odds ratio was computed for the variables which were significant in univariate analysis in order to ascertain the predictors of MetS. For regression analysis, variables were re-grouped as follows: educational status was grouped into three levels: (a) education level I – illiterate; (b) education level II – high, middle, and primary school education; and (c) education level III – profession or honors, graduate or post-graduate, and diploma. Occupational status was divided into the following three groups: (a) occupational group I – unemployed, homemakers, and students; (b) occupational group II – skilled, semi-skilled, and unskilled; and (c) occupational group III – profession, semi-profession, and shop-owner/clerk. Socioeconomic class was grouped into upper, middle, and lower class. Statistical significance was set at P value ≤ 0.05. Data analysis was performed using Microsoft Excel and Statistical Package for Social Sciences (SPSS for Windows, Version 17.0. SPSS Inc., Chicago, IL, USA).
| Results|| |
A total of 200 subjects were screened for inclusion in the study based on the specified criteria. Two subjects did not have a psychiatric diagnosis at the time of discharge and 13 subjects had been admitted more than once during the study period. Thus, 15 subjects were excluded from the study as per the exclusion criteria. A total of 185 subjects participated in the study. Of these subjects, 42 (22.7%) had MetS. The mean age of the subjects was 34.75 ± 11.05 years. Nearly 60% were males and 40% were females. Majority of the subjects who participated in the study were married (70.3%); belonged to upper lower class (31.4%); and hailed from rural areas (53.5%) [Table 1].
|Table 1: Association between sociodemographic variables and metabolic syndrome|
Click here to view
Higher age was associated with a higher prevalence of MetS (P = 0.001). There was a significant association between MetS and the following sociodemographic variables: educational status (P = 0.001), area of domicile (P = 0.003), and socioeconomic class (P = 0.001). Education levels II and III were 4.5 times and 8.8 times more likely to have MetS, respectively, in comparison to education level I. Subjects from urban areas had a 2.9 times higher risk of MetS in comparison to those from rural areas. Subjects from middle class and upper class were 25.8 and 30.5 times more likely to develop MetS, respectively, in comparison to those hailing from lower socioeconomic class [Table 2].
|Table 2: Predictors of metabolic syndrome with respect to sociodemographic variables|
Click here to view
A diagnosis of MetS was found among 16.4% of subjects with schizophrenia and other psychotic disorders; 12.5% of subjects with bipolar disorder; 21.1% with depressive disorder, 35% with alcohol use disorder and other substance use disorders (tobacco, cannabis, and opioids), and 28.6% of subjects with other psychiatric disorders (obsessive compulsive disorder, generalized anxiety disorder, conversion disorder, etc.). There was a significant association between MetS and alcohol use disorder and other substance use disorders (P = 0.029). Subjects with alcohol use disorder and other substance use disorders were 2.4 times more likely to have MetS [Table 3].
There was a significant association between the prevalence of MetS and longer duration of schizophrenia and other psychotic disorders (P = 0.000), depressive disorders (P = 0.04), and alcohol use disorder and other substance use disorders (P = 0.02) [Table 4].
|Table 4: Association between duration of psychiatric diagnosis and metabolic syndrome|
Click here to view
The distribution of various psychotropic drugs and its association with MetS is presented in [Table 5]. There was a significant association between the presence of MetS and intake of antipsychotics (P = 0.02), mood stabilizers (P = 0.05), and benzodiazepines (P = 0.04). Subjects on antipsychotics were 3.4 times more likely to have MetS than those not on antipsychotics.
|Table 5: Association between psychotropic medications and metabolic syndrome|
Click here to view
Using GPAQ, there was a significant association between level of physical activity and MetS (P = 0.001). A higher prevalence of MetS was noted among subjects with lower levels of physical activity. Subjects with high level of physical activity had a 64% reduced risk of having MetS in comparison to those with lower level of physical activity [Table 6].
|Table 6: Association between level of physical activity and metabolic syndrome|
Click here to view
| Discussion|| |
It is well known that mental and physical comorbidities co-exist and have a serious implication for the overall outcome of a patient. MetS increases morbidity and mortality, besides hampering patient adherence to psychotropic medication. Thus, a need arises to detect groups at high risk for developing MetS. In this study, we made an effort to explore the prevalence and correlates of MetS among psychiatric inpatients in a tertiary care hospital.
The strength of our study is that the sample contained a diagnostically heterogeneous population. This is advantageous because it serves to compare the prevalence of MetS among various psychiatric diagnostic groups. This is in contrast to many Indian studies in this field, which focus on a single psychiatric diagnosis.,, We also studied the association of MetS with several other variables such as sociodemographic variables, the duration of psychiatric illness, psychotropic medications prescribed, and level of physical activity. Level of physical activity in the context of mental illness is closely associated with MetS, but research is scarce on the same. We used a validated scale, the GPAQ, to assess the level of physical activity of the subjects.
In our sample, the overall prevalence of MetS was 22.7%. Other studies have reported similar findings., Nevertheless, this is lower than the prevalence of MetS found among hospitalized psychiatric patients. Interestingly, a community-based Indian study found a lower prevalence (3.9%) among untreated chronic schizophrenia subjects. An Australian study among patients with severe mental illness found a very high prevalence of MetS (54%), which was almost double that in the general population. The difference in prevalence between various studies suggests that geographic location, lifestyle, and cultural factors can influence the vulnerability for MetS.
In our study, the mean age of subjects with MetS was significantly higher compared to subjects without MetS. A possible explanations for this finding could be arterial structural change, age-related increase in abdominal circumference, poor nutrition, and poor exercise habits. We found higher rates of MetS among female subjects. Other researchers too have reported higher rates of MetS in females, especially with schizophrenia and recurrent major depressive disorder., There are studies which found no significant differences in the prevalence of MetS between men and women., The reasons for the gender differences are not clearly elucidated. Key gender differences in the prevalence of MetS seem to be related to distinctions in ethnicity, glycemic indices, body fat distribution, adipocyte size and function, hormonal regulation of body weight, and the influence of estrogen decline.,
We found a significant association between MetS and educational status. Patients with higher levels of education were more likely to develop MetS. A study in North India reported a similar finding. This is probably because of the association between lower educational status and manual labor occupations. However, several authors have not reported a relationship between MetS and educational level.,,,
In our study, subjects residing in urban areas had a 2.9 times higher risk of MetS. Our finding was in contrast to some studies where higher prevalence was found among those hailing from rural areas., An Indian general population-based study demonstrated a significantly lower prevalence of MetS in rural population. This could probably be attributed in general to urban lifestyle habits.
We found a higher prevalence of MetS among the upper socioeconomic class. Studies on various psychiatric cohorts, dating back to the early nineties, highlight the increased rate of obesity, due to poor diet and lack of exercise.,, Studies state that diet, obesity, and lack of employment vary with social class., A recent international study among subjects with severe mental illnesses stated that, many people with MetS are aware of their unhealthy diet, and this might provide a window of opportunity for lifestyle and dietary interventions.
In our study, subjects with alcohol use disorder and other substance use disorders were 2.4 times more likely to have MetS than those with other psychiatric diagnosis. Western studies reported a 5%–31% range for the prevalence of MetS among subjects consuming alcohol.,,,,,,,, The prevalence of MetS among outpatients and inpatients with substance use disorders was reported to be 13.6% and 24.6%, respectively., An American study found a consistent inverse dose–response relationship between alcohol consumption and MetS; they concluded that moderate and above moderate alcohol consumption impact metabolic health risk. Similar findings were documented in a recent meta-analysis. Alcohol is calorie dense, causes activation of sympathetic nervous system, reduces insulin sensitivity, and inhibits hepatic fatty acid oxidation, which contribute to MetS. Considering the high prevalence of alcohol consumption in this part of the country, additional emphasis needs to be placed on monitoring for MetS among those with alcohol use disorder.
Our study highlighted the association between longer duration of illness and the prevalence of MetS. Studies have stated that a key determinant for higher risk of MetS was longer illness duration.,,, Apart from exposure to psychotropic medications, prolonged mental illness can lead to chronic hypothalamo–pituitary–adrenal axis stress, resulting in physiological effects that are potently pro-inflammatory and anti-insulin.
We observed that subjects with intake of antipsychotics were 3.4 times more likely to have MetS than those who were not on antipsychotics. A meta-analysis reported that MetS risk differed significantly across commonly used antipsychotic medications. A study reported that 59.1% of patients with MetS were taking atypical antipsychotics compared to 39.5% among patients without MetS. A study reported an increased risk for MetS in patients with bipolar disorder and schizophrenia treated with second-generation antipsychotics. MetS components are more often present in patients treated with atypical antipsychotics; this effect is probably related to the receptor-binding profile of these drugs., Mental health professionals should be cognizant of the risk of development of MetS in patients on treatment with antipsychotics, in particular.
We found a significantly lower level of physical activity among subjects with MetS. There was a 64% reduced risk of having MetS among subjects with high level of physical activity. It has been demonstrated that schizophrenic patients with MetS are less physically active in daily life and have a reduced physical activity performance. On the contrary, some studies found no significant association between MetS and level of physical activity, in subjects with mental disorders., Symptoms such as anhedonia, fatigue, and disturbed bodily experiences, along with the sedative effects of various psychopharmacological treatments, may contribute to a sedentary lifestyle in psychiatric patients.
The pathophysiology underlying the association between mental disorders and MetS is complex and not well understood. Recent evidence suggests that they share pathophysiological features, including hypothalamic–pituitary–adrenal and mitochondrial dysfunction, neuro-inflammation, common genetic links, and epigenetic interactions.
Our study had some limitations such as the cross-sectional design, due to which subjects were not followed up to observe the course of MetS vis-a-vis the course of the mental disorder. As controls from the community were not part of the study design, the prevalence of MetS in the general population versus those with psychiatric disorders could not be compared. We only analyzed classes of drugs and not individual drugs. Analysis of individual drugs, the association between psychotropic medications (dose and duration) and MetS was hampered by poor treatment records, dose titration, and the simultaneous use of more than one drugs in certain subjects. We lacked a detailed dietary history, thereby precluding the study of influence of diet on MetS.
Research has focused predominantly on severe mental illness, and there is scanty research on other psychiatric disorders. Though studies on the international front are many, there are relatively less Indian studies. Studies in south India are especially sparse. In addition, there is extensive debate regarding the factors associated with high prevalence of metabolic disturbances in patients with severe mental illness. It is also well known that the coexistence of MetS and mental illness has an adverse impact on overall health outcomes. Further research can focus on a multi-centric design, prospective study, and a larger sample in order to elucidate the association between the course of mental disorders and course of MetS.
| Conclusion|| |
Our study showed that nearly one-fourth of psychiatric inpatients have MetS. This study provides additional evidence with regard to the prevalence of MetS among psychiatric inpatients. The risk profile depends on the sociodemographic profile, the psychiatric diagnosis, the duration of illness, the psychotropic medication used, and the level of physical activity. The pathophysiology underlying the association between mental disorders and MetS is complex and not well understood, and it requires further investigation.
Patients with mental illness should receive regular physical health checkups, be rigorously screened for MetS, and receive timely intervention. Additional emphasis is required with regard to the promotion of physical well-being and physical activity among patients with mental disorders. This will contribute to a better overall outcome.
The authors thank the patients and their caregivers for their active participation and kind cooperation. The authors acknowledge the services rendered by Dr. G. Ezhumalai, Senior Statistician and Research Consultant. I convey my sincere gratitude and thanks to Dr. Abu Backer, Senior Resident, and Mr. Rajkumar M., Psychologist, for translating the forms to Tamil. I extend my gratitute to Dr. Karthick Subramanian for his timely help.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Walker ER, McGee RE, Druss BG. Mortality in mental disorders and global disease burden implications: A systematic review and meta-analysis. JAMA Psychiatry 2015;72:334-41.
Brown S. Excess mortality of schizophrenia. A meta-analysis. Br J Psychiatry 1997;171:502-8.
Osborn DP, Levy G, Nazareth I, Petersen I, Islam A, King MB. Relative risk of cardiovascular and cancer mortality in people with severe mental illness from the United Kingdom's General Practice Rsearch Database. Arch Gen Psychiatry 2007;64:242-9.
Vancampfort D, Stubbs B, Mitchell AJ, De Hert M, Wampers M, Ward PB, et al
. Risk of metabolic syndrome and its components in people with schizophrenia and related psychotic disorders, bipolar disorder and major depressive disorder: A systematic review and meta-analysis. World Psychiatry 2015;14:339-47.
Kaur J. A comprehensive review on metabolic syndrome. Cardiol Res Pract 2014;2014:943162.
Padmavati R. Metabolic syndrome, serious mental illnesses & lifestyle. Indian J Med Res 2016;143:395-7.
] [Full text]
Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet 2005;365:1415-28.
Ramachandran A, Snehalatha C, Satyavani K, Sivasankari S, Vijay V. Metabolic syndrome in urban Asian Indian adults – A population study using modified ATP III criteria. Diabetes Res Clin Pract 2003;60:199-204.
Aguilar M, Bhuket T, Torres S, Liu B, Wong RJ. Prevalence of the metabolic syndrome in the United States, 2003-2012. JAMA 2015;313:1973-4.
Vancampfort D, Hallgren M, Mugisha J, De Hert M, Probst M, Monsieur D, et al
. The prevalence of metabolic syndrome in alcohol use disorders: A systematic review and meta-analysis. Alcohol Alcohol 2016;51:515-21.
Ganesh S, Ashok AH, Kumar CN, Thirthalli J. Prevalence and determinants of metabolic syndrome in patients with schizophrenia: A systematic review and meta-analysis of Indian studies. Asian J Psychiatr 2016;22:86-92.
Heiskanen T, Niskanen L, Lyytikäinen R, Saarinen PI, Hintikka J. Metabolic syndrome in patients with schizophrenia. J Clin Psychiatry 2003;64:575-9.
Elmslie JL, Silverstone JT, Mann JI, Williams SM, Romans SE. Prevalence of overweight and obesity in bipolar patients. J Clin Psychiatry 2000;61:179-84.
Skilton MR, Moulin P, Terra JL, Bonnet F. Associations between anxiety, depression, and the metabolic syndrome. Biol Psychiatry 2007;62:1251-7.
Mattoo SK, Singh SM. Prevalence of metabolic syndrome in psychiatric inpatients in a tertiary care centre in north India. Indian J Med Res 2010;131:46-52.
] [Full text]
John AP, Koloth R, Dragovic M, Lim SC. Prevalence of metabolic syndrome among Australians with severe mental illness. Med J Aust 2009;190:176-9.
Brown S, Birtwistle J, Roe L, Thompson C. The unhealthy lifestyle of people with schizophrenia. Psychol Med 1999;29:697-701.
Nyboe L, Lund H. Low levels of physical activity in patients with severe mental illness. Nord J Psychiatry 2013;67:43-6.
Newcomer JW. Metabolic syndrome and mental illness. Am J Manag Care 2007;13:S170-7.
Bermudes RA, Keck PE Jr., Welge JA. The prevalence of the metabolic syndrome in psychiatric inpatients with primary psychotic and mood disorders. Psychosomatics 2006;47:491-7.
Solia F, Rosso G, Maina G. Metabolic syndrome in acute psychiatric inpatients: Clinical correlates. J Psychopathol 2015;21:246-53.
Vancampfort D, Sweers K, Probst M, Maurissen K, Knapen J, Minguet P, et al
. Association of the metabolic syndrome with physical activity performance in patients with schizophrenia. Diabetes Metab 2011;37:318-23.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5). 5th
ed. Virginia: American Psychiatric Association; 2013.
Singh T, Sharma S, Nagesh S. Socio-economic status scales updated for 2017. Int J Res Med Sci 2017;5:3264.
Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al
. Harmonizing the metabolic syndrome: A joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009;120:1640-5.
Wanner M, Hartmann C, Pestoni G, Martin BW, Siegrist M, Martin-Diener E. Validation of the Global Physical Activity Questionnaire for self-administration in a European context. BMJ Open Sport Exerc Med 2017;3:e000206.
Grover S, Aggarwal M, Chakrabarti S, Dutt A, Avasthi A, Kulhara P, et al
. Prevalence of metabolic syndrome in bipolar disorder: An exploratory study from North India. Prog Neuropsychopharmacol Biol Psychiatry 2012;36:141-6.
Grover S, Aggarwal M, Dutt A, Chakrabarti S, Avasthi A, Kulhara P, et al
. Prevalence of metabolic syndrome in patients with schizophrenia in India. Psychiatry Res 2012;200:1035-7.
Grover S, Nebhinani N, Chakrabarti S, Avasthi A, Kulhara P, Basu D, et al
. Comparative study of prevalence of metabolic syndrome in bipolar disorder and schizophrenia from North India. Nord J Psychiatry 2014;68:72-7.
Kamkar MZ, Sanagoo A, Zargarani F, Jouybari L, Marjani A. Metabolic syndrome in patients with severe mental illness in Gorgan. J Nat Sci Biol Med 2016;7:62-7.
Centorrino F, Masters GA, Talamo A, Baldessarini RJ, Öngür D. Metabolic syndrome in psychiatrically hospitalized patients treated with antipsychotics and other psychotropics. Hum Psychopharmacol 2012;27:521-6.
Padmavati R, McCreadie RG, Tirupati S. Low prevalence of obesity and metabolic syndrome in never-treated chronic schizophrenia. Schizophr Res 2010;121:199-202.
Huang PL. A comprehensive definition for metabolic syndrome. Dis Model Mech 2009;2:231-7.
Lee NY, Kim SH, Jung DC, Kim EY, Yu HY, Sung KH, et al
. The prevalence of metabolic syndrome in Korean patients with schizophrenia receiving a monotherapy with aripiprazole, olanzapine or risperidone. Prog Neuropsychopharmacol Biol Psychiatry 2011;35:1273-8.
Pradhan AD. Sex differences in the metabolic syndrome: Implications for cardiovascular health in women. Clin Chem 2014;60:44-52.
Cardenas J, Frye MA, Marusak SL, Levander EM, Chirichigno JW, Lewis S, et al
. Modal subcomponents of metabolic syndrome in patients with bipolar disorder. J Affect Disord 2008;106:91-7.
Garcia-Portilla MP, Saiz PA, Benabarre A, Sierra P, Perez J, Rodriguez A, et al
. The prevalence of metabolic syndrome in patients with bipolar disorder. J Affect Disord 2008;106:197-201.
Salvi V, Albert U, Chiarle A, Soreca I, Bogetto F, Maina G. Metabolic syndrome in Italian patients with bipolar disorder. Gen Hosp Psychiatry 2008;30:318-23.
Sicras A, Rejas J, Navarro R, Serrat J, Blanca M. Metabolic syndrome in bipolar disorder: A cross-sectional assessment of a Health Management Organization database. Bipolar Disord 2008;10:607-16.
Prabhakaran D, Chaturvedi V, Shah P, Manhapra A, Jeemon P, Shah B, et al
. Differences in the prevalence of metabolic syndrome in urban and rural India: A problem of urbanization. Chronic Illn 2007;3:8-19.
Brugha TS, Wing JK, Smith BL. Physical health of the long-term mentally ill in the community. Is there unmet need? Br J Psychiatry 1989;155:777-81.
Kendrick T. Care of patients with schizophrenia. Br J Gen Pract 1993;43:259-60.
Bennett N, Dodd T, Flatley J, Freeth S, Bolling K. Health survey for England 1993.
Teixeira PJ, Rocha FL. The prevalence of metabolic syndrome among psychiatric inpatients in Brazil. Rev Bras Psiquiatr São Paulo Braz 2007;29:330-6.
Djoussé L, Arnett DK, Eckfeldt JH, Province MA, Singer MR, Ellison RC. Alcohol consumption and metabolic syndrome: Does the type of beverage matter? Obes Res 2004;12:1375-85.
Gigleux I, Gagnon J, St-Pierre A, Cantin B, Dagenais GR, Meyer F, et al
. Moderate alcohol consumption is more cardioprotective in men with the metabolic syndrome. J Nutr 2006;136:3027-32.
Yoon YS, Oh SW, Baik HW, Park HS, Kim WY. Alcohol consumption and the metabolic syndrome in Korean adults: The 1998 Korean National Health and Nutrition Examination Survey. Am J Clin Nutr 2004;80:217-24.
Zhu S, St-Onge MP, Heshka S, Heymsfield SB. Lifestyle behaviors associated with lower risk of having the metabolic syndrome. Metabolism 2004;53:1503-11.
Rosell M, De Faire U, Hellénius ML. Low prevalence of the metabolic syndrome in wine drinkers – Is it the alcohol beverage or the lifestyle? Eur J Clin Nutr 2003;57:227-34.
Santos AC, Ebrahim S, Barros H. Alcohol intake, smoking, sleeping hours, physical activity and the metabolic syndrome. Prev Med 2007;44:328-34.
Villegas R, Creagh D, Hinchion R, O'Halloran D, Perry IJ. Prevalence and lifestyle determinants of the metabolic syndrome. Ir Med J 2004;97:300-3.
Urashima M, Wada T, Fukumoto T, Joki M, Maeda T, Hashimoto H, et al
. Prevalence of metabolic syndrome in a 22,892 Japanese population and its associations with life style. Jpn Med Assoc J 2005;48:10.
Mattoo SK, Chakraborty K, Basu D, Ghosh A, Vijaya Kumar KG, Kulhara P. Prevalence & correlates of metabolic syndrome in alcohol & opioid dependent inpatients. Indian J Med Res 2011;134:341-8.
] [Full text]
Mattoo SK, Nebhinani N, Aggarwal M, Basu D, Kulhara P. Metabolic syndrome among substance dependent men: A study from north India. Ind Psychiatry J 2013;22:60-4.
] [Full text]
Churilla JR, Johnson TM, Curls R, Richardson MR, Boyer WR, Devore SR, et al
. Association between alcohol consumption patterns and metabolic syndrome. Diabetes Metab Syndr 2014;8:119-23.
Sun K, Ren M, Liu D, Wang C, Yang C, Yan L. Alcohol consumption and risk of metabolic syndrome: A meta-analysis of prospective studies. Clin Nutr 2014;33:596-602.
Wakabayashi I. Influence of age on the relationship between alcohol consumption and metabolic syndrome. Gerontology 2012;58:24-31.
Premarajan KC, Danabalan M, Chandrasekar R, Srinivasa DK. Prevalence of psychiatry morbidity in an urban community of Pondicherry. Indian J Psychiatry 1993;35:99-102.
] [Full text]
Grover S, Nebhinani N, Chakrabarti S, Avasthi A, Basu D, Kulhara P, et al
. Cardiovascular risk factors among bipolar disorder patients admitted to an inpatient unit of a tertiary care hospital in India. Asian J Psychiatr 2014;10:51-5.
Mitchell AJ, Vancampfort D, Sweers K, van Winkel R, Yu W, De Hert M. Prevalence of metabolic syndrome and metabolic abnormalities in schizophrenia and related disorders – A systematic review and meta-analysis. Schizophr Bull 2013;39:306-18.
Brunner EJ, Hemingway H, Walker BR, Page M, Clarke P, Juneja M, et al
. Adrenocortical, autonomic, and inflammatory causes of the metabolic syndrome: Nested case-control study. Circulation 2002;106:2659-65.
Correll CU, Frederickson AM, Kane JM, Manu P. Equally increased risk for metabolic syndrome in patients with bipolar disorder and schizophrenia treated with second-generation antipsychotics. Bipolar Disord 2008;10:788-97.
Nasrallah HA. Atypical antipsychotic-induced metabolic side effects: Insights from receptor-binding profiles. Mol Psychiatry 2008;13:27-35.
Dalacorte RR, Reichert CL, Vieira JL. Metabolic syndrome and physical activity in southern Brazilian community-dwelling elders: A population-based, cross-sectional study. BMC Public Health 2009;9:25.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]